prikaz prve stranice dokumenta Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia
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master's thesis
Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia
master's thesis
Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2019. urn:nbn:hr:169:056127
Miličević, Monika
University of Zagreb
Faculty of Mining, Geology and Petroleum Engineering
Department of Petroleum and Gas Engineering and energy

Institutional repository: Faculty of Mining, Geology and Petroleum Engineering Repository, University of Zagreb

Cite this document

Miličević, M. (2019). Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia : master's thesis (Master's thesis). Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:169:056127

Miličević, Monika. "Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia : master's thesis." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2019. https://urn.nsk.hr/urn:nbn:hr:169:056127

Miličević, Monika. "Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia : master's thesis." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2019. https://urn.nsk.hr/urn:nbn:hr:169:056127

Miličević, M. (2019). 'Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia : master's thesis', Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, accessed 10 October 2024, https://urn.nsk.hr/urn:nbn:hr:169:056127

Miličević M. Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia : master's thesis [Master's thesis]. Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering; 2019 [cited 2024 October 10] Available at: https://urn.nsk.hr/urn:nbn:hr:169:056127

M. Miličević, "Integration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia : master's thesis", Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:169:056127

Metadata
TitleIntegration of big data analysis and engineering advanced analytics to intelligently manage and control completion and artifical lift for selected well in Croatia : master's thesis
Title (croatian)Integracija "big data" analize i inženjerskog načina razmišljanja s ciljem upravljanja i kontroliranja inteligentnog opremanja i umjetnog načina podizanja nafte i plina za odabranu bušotinu s područja Hrvatske : diplomski rad
AuthorMonika Miličević
MentorBorivoje Pašić (mentor)
MentorMišo Soleša (mentor)
VIAF: 305474609
Committee memberBorivoje Pašić (predsjednik povjerenstva)
Committee memberVladislav Brkić (član povjerenstva)
Committee memberSonja Koščak Kolin (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Mining, Geology and Petroleum Engineering
(Department of Petroleum and Gas Engineering and energy)
Zagreb
Defense date and country2019-09-23, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mining, Petroleum and Geology Engineering
Petroleum Mining
Abstract
In order to reach more complex reservoir and increase ultimate recovery, engineers are searching for new technologies. One of these is intelligent completion which provides system monitoring, fluid production or injection control, and optimization. Operator can make decisions about managing completion based on real-time data coming from the downhole sensors. In addition, machine learning is becoming more popular in the oil industry. It finds application in automatization of processes and reducing time and error in decision making process. The aim of the thesis is to couple intelligent completion with machine learning (neural network) on the real example-gas well. The goal is to see if neural network can predict optimal interval control valve sizes for specific scenarios.
Abstract (croatian)
Inženjeri kontinuirano istražuju nove tehnologije kako bi razradili kompleksnija ležišta i povećali njihov ukupni iscrpak ležišta. Jedan od načina je i inteligentno opremanje koje pruža mogućnost daljinskog nadgledanja i kontrole cjelokupnog procesa pridobivanja ugljikovodika, te optimizaciju cijelog procesa. U takvom sustavu operator donosi odluke na temelju podataka koji dolaze u stvarnom vremenu sa senzora postavljenih u bušotinu. Nadalje, strojno učenje (engl. machine learning) postaje sve popularnije i u naftnoj industriji. Primjenjuje se u automatizaciji procesa kako bi se smanjilo vrijeme i greške prilikom donošenja odluka. Cilj ovoga rada je spojiti inteligentno opremanje sa neuronskom mrežom na stvarnom primjeru plinske bušotine. Uz to, cilj je vidjeti može li neuronska mreža predvidjeti optimalne veličine intervalnog kontrolnog ventila za različite slučajeve.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:169:056127
Study programmeTitle: Petroleum engineering; specializations in: Petroleum engineering, Energy production and supply, Environmental protection in petroleum engineering
Course: Petroleum engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka naftnog rudarstva (magistar/magistra inženjer/inženjerka naftnog rudarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-11-21 12:33:18